Evaluation and Modeling of Spoken Expression for Synthesis

One of the most pressing issues in modern studies of human-computer interaction is emotion-aware computing; a promising area of study that promises to provide major advances in the near future is genuine expressive speech synthesis. In this study, we detail our continuing efforts to construct expressive text-to-speech synthesis systems by creating a data-driven framework for annotation, modeling, and analysis of expressive speech. Here we detail the data-driven approach, which includes features like expression grouping and aural analysis as well as a web-based platform for voice recognition and annotation. There are also some promising signs for future study in the form of preliminary findings.